TAMING STOCHASTICITY: Evaluations & Observability at Scale

About this session

Your AI Shipped. Now What?Your AI passed the tests. The demo impressed stakeholders. The pilot delivered promising results. But what happens when real users arrive and your model behaves differently than expected? How do you know it is delivering consistent, reliable outcomes across different user groups and scenarios? And when performance drifts, safety issues emerge, or evaluations produce conflicting signals, do you have the visibility and infrastructure to understand why?Join us at AI4 to explore how leading enterprises are moving beyond manual evaluations, spreadsheets, and intuition to establish a rigorous, scalable approach for measuring and governing AI systems throughout their lifecycle. In this session, we will demonstrate how modern AI evaluation frameworks help organizations build confidence in production AI by combining persona-driven testing, customized evaluation methodologies, human oversight, and continuous monitoring into a single, integrated process.Learn how Persona Management enables teams to evaluate models against realistic user archetypes rather than relying on a single “average” user, uncovering biases, gaps, and performance variations before they impact customers. See how Bring Your Own Judges (BYOJ) allows organizations to define success on their own terms using domain-specific rubrics, custom scorers, fine-tuned classifiers, or external LLM judges that align with business objectives. Discover how a Jury of Evaluators creates stronger, more trustworthy assessments by aggregating multiple independent perspectives, reducing the risk of relying on a single evaluation metric or model.We will also showcase how Human-in-the-Loop workflows enable expert reviewers to focus on high-risk and low-confidence outcomes, while continuously improving automated evaluation mechanisms. In addition, attendees will learn how structured adversarial testing and red teaming can uncover vulnerabilities such as prompt injection attacks, jailbreak attempts, and edge-case failures before deploying solutions at scale.A key highlight of the session will be showcasing our enablement architecture, illustrating how evaluation, governance, and observability capabilities are embedded across the entire AI delivery lifecycle - from experimentation and development to deployment and production operations. Attendees will see how a unified architecture enables continuous validation, monitoring, and improvement of AI systems, providing actionable insights when model behavior changes and ensuring organizations maintain trust, compliance, and performance over time.Whether you are building AI-powered applications, deploying agents, or scaling generative AI across the enterprise, this session will provide practical strategies and architectural patterns to help you transform AI evaluation from an afterthought into a competitive advantage. Stop relying on guesswork. Start building AI systems you can measure, trust, and confidently scale.